Field of the Invention
The invention relates to an adaptive nonrecursive digital filter including a filter unit with N controllable filter coefficients, and a control unit controlling the filter coefficients as a function of an input signal applied to the filter unit, at a given sampling rate and as a function of a difference between a reference signal and an output signal output by the filter unit, in accordance with the least mean error square in each case.
The invention also relates to an adaptive nonrecursive digital filter including a signal processing device which, under program control from an input signal in combination with N controllable filter coefficients, generates an output signal, and in combination with a reference signal, in accordance with the least mean square error at the time, generates control signals for controlling the filter coefficients.
Adaptive digital filters are of major significance in many areas of discrete-time signal processing, particularly in the fields of system analysis, echo compensation at two-wire/four-wire junctions, removal of line distortion and speech processing. The characteristic of such adaptive digital filters, in comparison with constant digital filters, is that the filter parameters which determine the junction properties are adjusted optimally with respect to a quality functional. Such a quality function is achieved, for instance, due to the fact that the mean square error in the output signal of the adaptive digital filter relative to a reference signal is minimized.
That method, which is known generally as the least mean square algorithm, or LMS algorithm for short, is described by way of example in the book by B. Widrow and S. D. Stearns entitled "Adaptive Signal Processing", Prentice-Hall, Englewood Cliffs, N.J., 1985, particularly on pages 99-114. Page 290 of that same publication also shows a block diagram of the structure of an adaptive nonrecursive digital filter which operates according to the LMS algorithm. It includes a filter unit with a controllable filter coefficient, and a control unit that controls the filter coefficient both as a function of an input signal applied to the filter unit and as a function of the difference between a reference signal and an output signal output by the filter unit, in accordance with the least mean square error in each case.
The LMS algorithm is distinguished over other methods, such as the Newton method, by being less difficult and costly to achieve, but nevertheless it does not always have satisfactory convergence properties. Moreover, the LMS algorithm is based on the assumption of steady-state stochastic signals. This severely limits the field of application for adaptive nonrecursive digital filters operating by the LMS algorithm.
It is accordingly an object of the invention to provide an adaptive nonrecursive digital filter, which overcomes the hereinafore-mentioned disadvantages of the heretofore-known devices of this general type.